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Principal Engineer - AI
Irvine, California(onsite)
Canidate in PST time zone prefered
Principal AI Engineer to lead the architecture, strategy, and technical evolution of enterprise-scale AI platforms and GenAI-powered product experiences.
Key Responsibilities
Define and own enterprise AI platform architecture
Lead development of RAG pipelines and AI orchestration frameworks
Build production-grade AI systems and proofs of concept
Establish AI quality, evaluation, and governance standards
Drive AI platform design decisions and reusable tooling Required.
Technical Skills
Python engineering expertise
LLM applications, vector databases, retrieval infrastructure
LangChain, LlamaIndex, semantic search systems
AI evaluations, model lifecycle management, observability
Scalable GenAI systems and MLOps
Required Leadership Skills
12 years of software engineering experience, with significant tenure at Staff/Principal level.
Drive cross-team technical decisions, platform direction, and multi-team initiatives (architecture alignment, trade-off resolution, execution).
Define and scale AI-driven SDLC standards, including tools, guardrails, and automation patterns.
Hands-on experience with AI-assisted development (e.g., Copilot, Claude Code, Cursor) to deliver production systems; able to articulate workflow impact and guardrails.
Strong experience designing and evolving large-scale distributed systems (APIs, data pipelines, event driven systems, high-scale platforms).
Proven cross-org leadership driving architecture, standards, and platform initiatives across multiple teams.
Elevate engineering quality through code reviews, architecture reviews, and mentoring senior engineers.
Strong engineering fundamentals in code quality, testing, CI/CD, and observability while maintaining delivery velocity.
Effective communicator with the ability to influence stakeholders and drive alignment without formal authority.
Experience collaborating across product, data, security, and infrastructure teams.
Track record of documenting and scaling architectural decisions and organizational learnings.
Experience working with distributed teams (US, China, LATAM).
Principal Engineer - AI
Irvine, California(onsite)
Canidate in PST time zone prefered
Principal AI Engineer to lead the architecture, strategy, and technical evolution of enterprise-scale AI platforms and GenAI-powered product experiences.
Key Responsibilities
Define and own enterprise AI platform architecture
Lead development of RAG pipelines and AI orchestration frameworks
Build production-grade AI systems and proofs of concept
Establish AI quality, evaluation, and governance standards
Drive AI platform design decisions and reusable tooling Required.
Technical Skills
Python engineering expertise
LLM applications, vector databases, retrieval infrastructure
LangChain, LlamaIndex, semantic search systems
AI evaluations, model lifecycle management, observability
Scalable GenAI systems and MLOps
Required Leadership Skills
12 years of software engineering experience, with significant tenure at Staff/Principal level.
Drive cross-team technical decisions, platform direction, and multi-team initiatives (architecture alignment, trade-off resolution, execution).
Define and scale AI-driven SDLC standards, including tools, guardrails, and automation patterns.
Hands-on experience with AI-assisted development (e.g., Copilot, Claude Code, Cursor) to deliver production systems; able to articulate workflow impact and guardrails.
Strong experience designing and evolving large-scale distributed systems (APIs, data pipelines, event driven systems, high-scale platforms).
Proven cross-org leadership driving architecture, standards, and platform initiatives across multiple teams.
Elevate engineering quality through code reviews, architecture reviews, and mentoring senior engineers.
Strong engineering fundamentals in code quality, testing, CI/CD, and observability while maintaining delivery velocity.
Effective communicator with the ability to influence stakeholders and drive alignment without formal authority.
Experience collaborating across product, data, security, and infrastructure teams.
Track record of documenting and scaling architectural decisions and organizational learnings.
Experience working with distributed teams (US, China, LATAM).